Diffusion Sign Subband Adaptive Filtering Algorithm with Enlarged Cooperation and Its Variant

Abstract

The recently proposed diffusion sign subband adaptive filtering (DSSAF) algorithm is more robust than most of mean-square error minimization criterion-based diffusion distributed estimation algorithms in an impulsive interference environment. To enhance its convergence rate and steady-state misalignment, this paper proposes a DSSAF algorithm with enlarged cooperation (DSSAF-EC). The DSSAF-EC algorithm exchanges not only the weight information but also measurements within individual neighborhoods. Moreover, a variant of the DSSAF-EC algorithm, called the proportionate DSSAF-EC (PDSSAF-EC) algorithm, is presented. It incorporates an adaptive gain matrix into the DSSAF-EC algorithm to proportionately adapt the weight vectors of agents. Simulation results verify that both the DSSAF-EC and PDSSAF-EC algorithms are robust against impulsive interference and that the PDSSAF-EC algorithm can obtain faster convergence rate than the DSSAF-EC algorithm in estimating a sparse unknown weight vector.